code: def store_model_indicators(
      model: torch.nn.Module, *, model_name: str = "model"
  ):
      """
      Track model parameters and gradients.
  
      Arguments:
          model (Optimizer): PyTorch model
  
      Keyword Arguments:
          model_name (str, optional): name of the model
      """
      for name, param in model.named_parameters():
          if param.requires_grad:
              with torch.no_grad():
                  store_l1_l2(f"param.{model_name}.{name}", param)
                  if param.grad is not None:
                      store_l1_l2(
                          f"grad.{model_name}.{name}", param.grad
                      )
  
file_path: labml/client/labml/utils/pytorch.py
imports: from typing import Optional, Dict, TYPE_CHECKING
  import torch
  from labml import tracker
  from labml.configs import BaseConfigs
label_desc: Use image node_id 3 for calling a global function with example usage: store_model_indicators(model) without return types